Abstract: Methods for enhancing compatibility of a document of an entity with an organization's database on a computer server to facilitate detection of a fraudulent submission. Methods may include receiving a populated document in a first format from the entity, using a processor to digitize the document into a digital format, such as bytes, and further into a second format, where the first format may not be compatible with the database and the second format may be compatible with the database. Methods may include using the processor, optionally running a statistical model, to determine an entity identifier, a predicted value of a data field in the document, and whether there is a difference between the value in the predicted data field and a corresponding value in the populated document. Methods may include implementing a corrective action, such as raising a fraud alert at the organization, when there is a difference.

Abstract: A content recommendation system includes a computing platform having a hardware processor and a system memory storing a content surfacing software code providing a user interface. The hardware processor executes the content surfacing software code to receive an initiation signal identifying a user, and, in response, identify content items as desirable content items to the user based on the user and metadata describing each of the desirable content items. In addition, the content surfacing software code generates a networked map of nodes corresponding respectively to the desirable content items, where the distances between nodes are based on the similarity of the metadata describing the desirable content items corresponding to the nodes. The content surfacing software code further outputs the networked map for display to the user via the user interface, the nodes being displayed as thumbnail images depicting the desirable content and selectable by the user.

Abstract: A method includes obtaining matches between target records in a target dataset and a reference records in a reference dataset, each match of the matches comprising a corresponding confidence level of the match, categorizing the target records into review level categories according to the corresponding confidence level, and presenting a graphical user interface (GUI). The GUI includes a first section for a first review level category showing a first subset of the target records assigned to the first review level category, the first subset comprising target records related, in the GUI, to at least one matching reference record. The GUI includes a second section for a second review level category, wherein the second section shows a second subset of the target records assigned to the second review level category, the second subset comprising target records related, in the GUI, to at least one matching reference record.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: training a visual similarity model to output one or more vector representations in a vector space; determining one or more nearest neighbors based on embeddings nearest to a respective embedding in the vector space for the item; ranking the one or more nearest neighbors for the item in an order; re-ranking the order of the one or more nearest neighbors of the item into a re-ranked order; inserting, into a display of the item, the one or more nearest neighbors of the item; and facilitating altering a graphical user interface (GUI) to convey the display of the item. Other embodiments are disclosed herein.

Abstract: Techniques, described herein, include solutions for anonymous geospatial evaluation via a wireless network. For example, a user equipment (UEs) may monitor a current location of UE for entry into a bounding box associated with a geographic area. Upon entry, the UE may generate and report an anonymous presence indicator to a bounding box server via the wireless network. The anonymous presence indicator may include information describing an instance of a UE being located within the bounding box; however, the anonymous presence indicator may not include information indicating an identifier of UE and/or a user of UE. The UE may report another anonymous presence indicator upon expiration of a re-report timer and/or upon entry into another bounding box.

Abstract: A method and device of similarity determination, network training, and search, an electronic device, and a storage medium are provided. The data similarity determination method includes: acquiring first data of a first object; mapping the first sub-data as a first semantic representation in a semantic comparison space, where the semantic comparison space enables a similarity between a semantic representation obtained by mapping data of the first modality to the semantic comparison space and a semantic representation obtained by mapping data of the second modality to the semantic comparison space to be computed; acquiring second data of a second object; mapping the second sub-data as a second semantic representation in the semantic comparison space; and calculating a similarity between the first data and the second data based on at least the first semantic representation and the second semantic representation.

Abstract: A computer-implemented method includes determining a set of identigens for each word of patent claim elements to produce sets of identigens and interpreting pairs of adjacent identigens of adjacent sets of identigens to determine a most likely meaning of the claim elements and produce a claim entigen group. The method further includes determining a level of match between the claim entigen group and a comparison matter entigen group. When the level of match between the claim entigen group and the comparison matter entigen group is greater than a threshold level, the method further includes indicating potential utilization of the claim by the comparison matter or potential prior art status of the comparison matter.

Abstract: In some embodiments, a method receives query content that includes first visual data and select reference content that includes second visual data. A first visual feature mapping for the query content is generated using a model that is trained to generate visual feature mappings using content pairs where alterations in one instance of the content pair are used in the training. A second visual feature mapping is determined for the reference content. The second visual feature mapping is determined using the model. The method compares the first visual feature mapping and the second visual feature mapping to generate a score that rates a similarity between the query content and the reference content. The score is based on recognizing an alteration in one instance of the query content and the reference content. The score is output.

Abstract: Systems and methods include using a clustering engine to determine topics in a communication. An example system includes a user interface module that receives user input relating to a criteria to define a set of communications, wherein the criteria is at least one of a category, a score, a sentiment, an agent, an agent grouping, a speaker, a location, an event attribute, a call center, a time of communication, or a date of communication, an acoustic analysis module that analyzes the set of communications to determine one or more acoustic characteristics of one or more communications in the set of communications, and a clustering engine that analyzes words and phrases in the set of communications and the one or more acoustic characteristics, and to determine a topic of the set of communications based on at least one commonality in words, phrases, or the one or more acoustic characteristics.

Abstract: A computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location and manage the dynamic queue by routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs by transmitting updated navigation-related data to one or more of the matched transport providers.

Abstract: According to an embodiment, an electronic apparatus includes a plurality of service engines corresponding to a plurality of speech recognition services, respectively; a communication module connected via wireless communication to a plurality of service servers for providing the plurality of speech recognition services, respectively; a mike configured to receive speech of a user; and a service controller configured to store at least one wakeup word corresponding to each of the plurality of speech recognition services in advance, determine a speech recognition service corresponding to a wakeup word received by the mike from among the plurality of speech recognition services based on the plurality of wakeup words stored in advance, send a user command received by the mike to a service engine corresponding to the determined speech recognition service among the plurality of service engines.

Abstract: A virtual environment may be generated, the environment including a procedurally generated virtual property. The virtual property may include various features automatically generated based upon a procedural rule set, so as to provide variability between two or more virtual properties. One or more procedurally generated virtual properties may be provided to a user, and various virtual tools may be provided via which the user may identify relevant aspects corresponding to risk associated with the virtual property.

Abstract: Provided are a watermark adding method and apparatus, a storage medium and a device. The method includes steps described below. To-be-added watermark information is acquired, and a time offset is determined according to the watermark information; a video frame rate is acquired, and time information of a frame image in a video is determined according to the video frame rate; and offset processing is performed on the time information according to the time offset to add the watermark information to the video.

Abstract: Systems and methods for implementing a representative support system in a task determination system are provided. The task determination system automatically receives in real-time a set of messages between a member and a representative as these messages are exchanged. The set of messages correspond to a set of proposals associated with a task. The task determination system automatically identifying a selection of a proposal from the set of proposals based on an analysis of the set of messages. Based on the selection, the task determination system generates a set of proposal tasks and processes communications associated with these proposal tasks to monitor performance of these proposal tasks for completion of the task.

Abstract: Computer-readable media, methods, and systems for comparing and migrating multiple online user accounts from multiple online platforms while reducing the probability of false mergers. At least one first online platform comprising a plurality of online accounts associated with the first online platform may be compared with at least one second online platform comprising a plurality of online accounts associated with the second online platform. The comparison further includes comparing the one or more fields of personally identifiable information associated with the first user and the one or more fields of personally identifiable information associated with the second user while excluding known improbable values. Following the comparison between the online accounts, a migration outcome may be determined for creating a new online account, migrating online accounts across online platforms, or consolidating online accounts.

Abstract: A system for phishing website classification accesses a first website that is known to be a phishing website. The system extracts images from the first website, and generates a hash value for each image. The system generates a first overall hash value for the website by hashing the hash values. The system accesses a list of plurality of phishing websites, each is associated with a different overall hash value from among a plurality of overall hash values. The system compares the first overall hash value with a second overall hash value associated with a particular phishing website. The system determines whether the first overall hash value corresponds to the second overall hash value. If it is determined that the first overall hash value corresponds to the second overall hash value, the system classifies the first website to a phishing website class that the particular phishing website belongs.

Abstract: A system determines that a first data element in a first message is linked to a first data field in a first mapped dataset. The system receives a request to determine to which data field in a second mapped dataset a second data element in a second message should be mapped. The system extracts a first set of features from the first message. The system determines that the first data element is located on a first location within the first message. The system extracts a second set of features from the second message. The system determines that the second data element is location on a second location within the second message. The system determines a difference between the first location and the second location. If the difference is less than a threshold distance, the system associates the second data element to the first data element in the second mapped dataset.

Abstract: In one embodiment, a first entry in a first database is modified to include data from a highest-ranked one of one or more available data tables that correspond to the first entry. Each of one or more characters fields of the modified first entry are converted into a respective one or more first-entry tokens, and each of one or more character fields of each of a plurality of second entries in a second database is converted into a respective one or more second-entry tokens. The first-entry tokens are compared to the second-entry tokens, and, in response to the comparison, it is determined whether the first entry matches one of the second entries. In response to determining that the first entry matches one of the second entries, the first entry and the matching second entry are associated with one another in one or both the first and second databases.

Abstract: The model generation platform enables generation of machine learning models based on modular storage of user-specified training data. The platform can obtain a dataset from a different heterogenous source (e.g., a structured database, an unstructured database, a semi-structured file system, manual upload of a comma-separated value file, a spreadsheet, and/or big data) through an associated application programming interface and store this data in a first storage medium. The model generation platform can obtain an indication of a portion of the dataset from a user via a user interface and determine a second storage medium for this portion of the dataset based on an associated estimated performance metric. In response to a request for generation of a machine learning model, the model generation platform can generate a machine learning model using training data comprising a subset of the portion of the dataset.

Abstract: Systems, apparatuses, and methods are provided for determining a bid value for placing an advertisement onto advertising space available through an electronic marketplace. A method is used for calculating the option value of maintaining the advertisement in the advertising space during one or more periods of time. The option value may be based on expected profits and the estimated future value of maintaining the advertisement. The option value may then be used to calculate the bid price for placing the advertisement.

Abstract: A method for processing images includes: determining an image attribute of each image block of a plurality of image blocks in a to-be-processed image, determining a filter model corresponding to each of the image blocks based on the image attribute of each of the image blocks, and acquiring a filtered image of the to-be-processed image by filtering each of the image blocks by the filter model corresponding to each of the image blocks.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate automatic identification of a set of fact-check factors from digital documents. Digital documents can be identified from a plurality of sources. For each digital document, a set of fact check factors are identified using a trained sequence tagging model. Based on the sequence tagging model, a confidence value representing a likelihood that the set of fact check factors identified from the digital document are an actual set of fact check factors for the digital document is determined. The set of fact check factors is stored in association with the digital document. A request for fact check factors for a particular digital document among the digital documents is received from a fact checking entity. In response, the set of fact check factors identified from the particular digital document are provided to the fact checking entity.

Abstract: A method includes receiving an object from a client as part of a data ingestion process, by a masker worker, generating a list that identifies one or more byte ranges, of the object, to be masked, providing the list to an object access microservice, by the object access microservice, creating an object recipe of the object, and the object recipe includes one or more slices, and each of the slices includes one or more segments of data, masking only those segments of a slice that are in a byte range identified in the list, creating a masked slice that comprises the masked segments, and creating a masked object recipe that contains a reference to the masked slice, and the masking is performed before the object is stored in storage, creating a masked object that includes the masked slice, and deduplicating the masked object.

Abstract: Example aspects include techniques for creating video stickers from user-generated content. These techniques may include receiving selection of a video content item previously uploaded to a SMP server application corresponding to the SMP client application, and presenting a graphical user interface (GUI) for receiving one or more derivative attributes for generating a derivative video sticker from the video content item. In addition, the techniques may include adding the derivative video sticker to a library of stickers provided by the SMP server application to a plurality of SMP client applications, and presenting the derivative video sticker within a communication interface associated with the SMP server application.

Abstract: A computer-implemented method of matching a customer with a service provider, the method comprising: creating, by a computing device, a profile of a customer having a plurality of categorical values descriptive of or liked by the customer; creating, by the computing device, a profile of a service provider having a plurality of categorical values descriptive of or liked by the service provider; creating, by the computing device, a request by the customer to recommend a service provider, wherein the request includes one or more requested categorical and discrete values; and providing, by the computing device, ranked recommendations of service providers to the customer based on a comparison of the categorical values in the profiles of the customer and the service provider and the requested categorical and discrete values by the customer. A service provider can be a hair stylist.

Abstract: A method for removing uninterested attributes from multi-modality data may include: receiving, by a multi-modality attribute removal computer program executed by an electronic device, multi-modality data comprising a plurality of modalities from a data source, wherein data in each modality are related; receiving, by the multi-modality attribute removal computer program, an uninterested attribute in the multi-modality data to remove; training, by the multi-modality attribute removal computer program, a modality-focused encoder for each modality of the multi-modality data to remove the uninterested attribute using a removal loss and a retention loss for the respective modality; receiving, by the multi-modality attribute removal computer program, a multi-modality data set for processing; and processing, by the multi-modality attribute removal computer program, the multi-modality data set using the modality-focused encoders, wherein the processing results in a processed multi-modality data set with the uninterest

Abstract: A method includes receiving a first document, the first document including multiple sections, each of the multiple sections tagged with metadata indicating a relationship with a department of an organization; receiving a second document, the second document including multiple sections, each of the multiple sections tagged with metadata indicating a relationship with the department of the organization; comparing the sections of the first document tagged with metadata indicating the relationship of the first document with the department with the sections of the second document tagged with metadata indicating the relationship of the second document with the department to determine differences between the department-relevant sections of the first document and the department-relevant sections of the second document; and presenting the differences between the department-relevant sections to a user in a document difference viewer.

Abstract: A method includes receiving a query directed to a first data model that specifies base data fields. The method includes determining extension bindings for the first data model. A binding specifies an extension to the first data model and specifies one of the base data fields as a node at which the specified extension is added. The extension specifies a non-empty set of data fields. The method includes retrieving base data values according to the base data fields and extension data values according to, for a first binding, the set of data fields. The method includes generating a data object from the base and extension data values according to a second data model. The second data model is based on the first data model extended by adding the data fields from the extension specified by the first binding to the first data model at the specified node.

Abstract: A cloud platform establishes a communication session between an agent and a user. The communication session is over an electrical medium. The cloud platform generates an interface on a client device associated with the agent. A first portion of the interface is configured to exchange messages between the agent and the user for a conversation or otherwise transcribe a conversation between the agent and the user. The cloud platform obtains, at a first time, a set of utterances from a transcript of the conversation. The cloud platform accesses a database including a plurality of articles. The cloud platform generates relevance scores between the conversation and the plurality of articles. The cloud platform then selects a subset of articles having relevance scores above a threshold value or proportion. The identified articles are presented on a second portion of the interface.

Abstract: A system and method is provided for an automated online reputation monitoring and intelligence gathering solution that also provides services that manage a reputation once content damaging to the reputation has been identified. Functions and services of the automated online reputation monitoring and intelligence gathering solution include the aggregation of information from non-proprietary websites and social networks, the ability to contact support for assistance with reputation management, the ability to submit requests to fix online reputation, and the delivery of alerts directly to a user device.

Abstract: Systems, methods, and non-transitory computer-readable storage media are provided for predicting the likelihood or probability of a subscriber of a service to cancel or not renew a subscription. A method, according to one implementation, includes a step of receiving data pertaining to aspects of a service that is provided by a service provider to a subscriber in accordance with a subscription. The data may include one or more impact factors each having a positive, neutral, or negative influence on the likelihood of subscriber churn. The method also includes a step of using the one or more impact factors to predict the likelihood that the subscriber will cancel the subscription.

Abstract: In some embodiments, a processor receives natural language data for performing an identified cybersecurity task. The processor can provide the natural language data to a first machine learning (ML) model. The first ML model can automatically infer a template query based on the natural language data. The processor can receive user input indicating a finalized query and to provide the finalized query as input to a system configured to perform the identified computational task. The processor can provide the finalized query as a reference phrase to a second ML model, the second ML model configured to generate a set of natural language phrases similar to the reference phrase. The processor can generate supplemental training data using the set of natural language phrases similar to the reference phrase to augment training data used to improve performance of the first ML model and/or the second ML model.

Abstract: Adjusting an operating frequency of a CPU includes setting the operating frequency for a current operating cycle based on a CPU load in a prior operating cycle and a target CPU load. A current CPU load associated with the current processing cycle is detected. The CPU operating frequency is adjusted to a new operating frequency based on a difference between the target CPU load and the current CPU load. The operating frequency is adjusted based on minimizing the difference between the target CPU load and the detected load. A CPU load error is determined based on the current CPU load and the target CPU load. The target CPU load is adjusted based on the determined CPU load error and a threshold load error. A prediction is generated on whether to perform a new adjustment of the operating frequency of the CPU prior to expiration of a threshold time duration.

Abstract: A system and method for chatbot and search engine integration comprising chatbot crawler engine configured to detect all possible paths through a conversational flow between a chatbot and a user, and also comprising a chatbot search integration manager configured to receive a processed conversation flow from the chatbot crawler engine, parse the conversation flow to identify keywords and features, and build an indexable data structure which can be integrated into search engines in order to expose the information and data contained within the chatbot's knowledge base. This integration may allow search engine users to be redirected to a website hosting the chatbot when an indexed data structure comprises information relevant to a search engine query.

Abstract: Predicting potential policy violations in a given data source (such as a set of documents) so that a deeper analysis can be performed on the set of documents to gain additional insights into the potential policy violation(s) that may be contained therein. In some instances, this prediction is done by performing a random sampling operation on the set of documents and collecting the metadata from these documents in order to determine whether or not the set of documents that are randomly sampled include a policy violation that can be remediated.

Abstract: Systems and methods for generating prompts for user data entry can include obtaining context data. The context data can be processed to determine whether an input entry interface is to be provided. In response to determining an input entry interface is to be provided, the context data or other data associated with a content display instance can be processed with a generative model to generate a prompt that can be provided to the user. User input data can then be obtained and stored to be provided to other users.

Abstract: Methods and systems for filtering video content items are described herein. The system identifies a plurality of video content items that are linked to respective image content items. The system determines, for each of the plurality of video content items, whether a video content item corresponds to a respective image content item. In response to the determining, the system causes to be provided information identifying the plurality of video content items excluding video content items that do not correspond to respective image content items.

Abstract: Systems and methods are described herein relating to ingesting data objects from various sources and associating them in a hierarchy with a profile. In some aspects, a data object, including a set of fields and indicating a data object type, may be obtained for associating with a profile maintained by a computing resource service provider. The data object may be converted into a standardized format based on the data object type indicated in the data object using an object mapping associated with the data object. A key associated with the data object and indicated in the object mapping may be selected and used to search an index for a related profile. Upon finding a profile with the matching key, the profile may be updated to include an association of the standardized data object, such as in a hierarchy.

Abstract: A query directed to database data stored across a set of files is received. The query includes predicates applied against metadata of the set of files. One or more files are removed from the set of files whose metadata does not satisfy a predicate of the plurality of predicates. Rows of the one or more remaining files of the set of files are filtered based on the one or more predicates.

Abstract: A learning apparatus, a walking training apparatus, a method, a system, a program, and a trained model for performing walking training at appropriate setting parameters are provided. A learning apparatus according to an embodiment includes: a data acquisition unit configured to acquire rehabilitation data from a walking training apparatus including an actuator configured to assist a walking motion of a trainee and a control unit configured to control the actuator in accordance with a setting parameter; and a data generation unit configured to generate an index indicating a degree of recovery of the trainee and the setting parameter as learning data; and a learning unit configured to generate a learning model that receives the index and outputs a recommended value of the setting parameter by performing machine learning using the learning data.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The present disclosure relates to driver interaction with a user interface of a vehicle. In particular, the present disclosure relates to an apparatus for performing an action associated with a driver input indicated via an input modality of an HMI of a vehicle, the apparatus comprising processing circuitry configured to receive initial data corresponding to an initial driver input via a first input modality of the HMI of the vehicle, compare a confidence level of the initial data to a confidence level threshold associated with the first input modality of the HMI of the vehicle, request, based on the comparison, a subsequent driver input via a second input modality of the HMI of the vehicle, determine a presence of an adverse condition within a vehicle environment, and perform an action associated with the subsequent driver input based on the presence of the adverse condition within the vehicle environment.

Abstract: Systems and methods are described for procedurally-based decision support using ontology-based classification of database records. The procedural decision support can facilitate extraction of contextually relevant data from a database. The data may be formatted for compatibility with a knowledge-based data library using one or more scripts and populated in the library as an entity. Classification of the entity can be reasoned using the available data. One or more classifications of the entity may be returned to the procedural decision support to facilitate computation of a recommendation.

Abstract: Systems and methods for personalized device routines include determining devices associated with user account data and generating device usage data indicating aspects of smart device usage over a period of time. The usage data may then be utilized to identify candidate smart devices, time indicators, and trigger event types to associate with candidate routines. One or more of the candidate routines may be recommended to a user based at least in part on the usage data and the trigger event types at issue to personalize the device routine recommendations.

Abstract: Provided is an information processing apparatus including a first dictionary that has registered a plurality of utterance expressions, a first voice recognition unit that executes a first voice recognition process using the first dictionary, and a dictionary update unit that updates utterance expressions to be registered to the first dictionary based on usage performance of utterance of a user, in which the dictionary update unit deletes an utterance expression having a low usage performance of utterance from the first dictionary or transfers the utterance expression to a second dictionary that has registered a plurality of utterance expressions not registered in the first dictionary.

Abstract: Some embodiments are directed to a requesting device and a data device configured for multi-party computation to select a close record from a database. The data device performs a filtering of its candidate records by selecting candidate records from the database for which a received set of similarity values for a target record are close to a set of similarity values for a candidate record. For one or more selected candidate records, the requesting device and the data device performing a multiparty computation protocol to jointly compute a second closeness measure between the target record and the selected candidate record.

Abstract: An apparatus and a method for cybersecurity, the apparatus comprising a processor being configured to execute instructions in a memory to control the apparatus to receive an input for a subject address in a target blockchain system and to obtain a list of addresses involved in a predefined number of hops of transactions upstream and/or downstream of the subject address in the target blockchain system. Suspicious transaction behaviour of addresses in the obtained list of addresses upstream and/or downstream of the subject address are identified by the apparatus. A risk score indicative of degree of cybersecurity threat for the subject address taking into consideration the suspicious transaction behaviour is then calculated.

Abstract: A method comprises computing a hash value for at least one file of a plurality of files in connection with a file tiering operation of the plurality of files from a source storage location to a target storage location. The hash value is compared to one or more hash values corresponding to one or more other files of the plurality of files. Based at least in part on the comparing, a determination is made whether the hash value is the same as any of the one or more hash values. The at least one file is identified as a duplicate file in response to an affirmative determination. The target storage location comprises a cloud storage platform.

Abstract: A method for alerting a user of a clinical pathways management system to a clinical pathway deviation, comprising: (i) providing a reference ontology comprising information about a plurality of clinical pathways; (ii) defining a domain ontology; (iii) converting the domain ontology to one or more graphical representations of clinical pathways; (iv) generating one or more deviation rules for the clinical pathways; (v) receiving information about one or more interventions relative to a patient being treated using a first clinical pathway; (vi) identifying, by comparing the received information about one or more interventions with the one or more deviation rules for the first clinical pathway, one or more deviations from the first clinical pathway; and (vii) alerting the user of the clinical pathways management system to the identified one or more deviations from the first clinical pathway.

Abstract: Approaches herein transparently delegate data access from a relational database management system (RDBMS) onto an offload engine (OE). The RDBMS receives a database statement referencing a user defined function (UDF). In an execution plan, the RDBMS replaces the UDF reference with an invocation of a relational operator in the OE. Execution invokes the relational operator in the OE to obtain a result based on data in the OE. Thus, the UDF is bound to the OE, and almost all of the RDBMS avoids specially handling the UDF. The UDF may be a table function that offloads a relational table for processing. User defined objects such as functions and types provide metadata about the table. Multiple tables can be offloaded and processed together, such that some or all offloaded tables are not materialized in the RDBMS. Offloaded tables may participate in standard relational algebra such as in a database statement.